Cited by 599Obesity, Physical Activity, DietStatistical Methods in EpidemiologyBody Composition Measurement Techniques

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Accuracy and usefulness of BMI measures based on self-reported weight and height: findings from the NHANES & NHIS 2001-2006

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Stommel, Manfred, Schoenborn, Charlotte A·2009·BMC Public Health

DOI 10.1186/1471-2458-9-421PMC PMC2784464

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Abstract

BACKGROUND: The Body Mass Index (BMI) based on self-reported height and weight ("self-reported BMI") in epidemiologic studies is subject to measurement error. However, because of the ease and efficiency in gathering height and weight information through interviews, it remains important to assess the extent of error present in self-reported BMI measures and to explore possible adjustment factors as well as valid uses of such self-reported measures. METHODS: Using the combined 2001-2006 data from the continuous National Health and Nutrition Examination Survey, discrepancies between BMI measures based on self-reported and physical height and weight measures are estimated and socio-demographic predictors of such discrepancies are identified. Employing adjustments derived from the socio-demographic predictors, the self-reported measures of height and weight in the 2001-2006 National Health Interview Survey are used for population estimates of overweight & obesity as well as the prediction of health risks associated with large BMI values. The analysis relies on two-way frequency tables as well as linear and logistic regression models. All point and variance estimates take into account the complex survey design of the studies involved. RESULTS: Self-reported BMI values tend to overestimate measured BMI values at the low end of the BMI scale (< 22) and underestimate BMI values at the high end, particularly at values > 28. The discrepancies also vary systematically with age (younger and older respondents underestimate their BMI more than respondents aged 42-55), gender and the ethnic/racial background of the respondents. BMI scores, adjusted for socio-demographic characteristics of the respondents, tend to narrow, but do not eliminate misclassification of obese people as merely overweight, but health risk estimates associated with variations in BMI values are virtually the same, whether based on self-report or measured BMI values. CONCLUSION: BMI values based on self-reported height and weight, if corrected for biases associated with socio-demographic characteristics of the survey respondents, can be used to estimate health risks associated with variations in BMI, particularly when using parametric prediction models.

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Additional file 6 of Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
Pelgrims, I., Devleesschauwer, B., Vandevijvere, S., Clercq, E. M. D., Vansteelandt, S., Gorasso, V., & der Heyden, J. V. (2024) · Figshare · doi:10.6084/m9.figshare.26577773
Additional file 14 of Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
Pelgrims, I., Devleesschauwer, B., Vandevijvere, S., Clercq, E. M. D., Vansteelandt, S., Gorasso, V., & der Heyden, J. V. (2024) · Figshare · doi:10.6084/m9.figshare.26577797
Additional file 8 of Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
Pelgrims, I., Devleesschauwer, B., Vandevijvere, S., Clercq, E. M. D., Vansteelandt, S., Gorasso, V., & der Heyden, J. V. (2024) · Figshare · doi:10.6084/m9.figshare.26577779
Additional file 20 of Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
Pelgrims, I., Devleesschauwer, B., Vandevijvere, S., Clercq, E. M. D., Vansteelandt, S., Gorasso, V., & der Heyden, J. V. (2024) · Figshare · doi:10.6084/m9.figshare.26577815
Additional file 19 of Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
Pelgrims, I., Devleesschauwer, B., Vandevijvere, S., Clercq, E. M. D., Vansteelandt, S., Gorasso, V., & der Heyden, J. V. (2024) · Figshare · doi:10.6084/m9.figshare.26577812
Additional file 15 of Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
Pelgrims, I., Devleesschauwer, B., Vandevijvere, S., Clercq, E. M. D., Vansteelandt, S., Gorasso, V., & der Heyden, J. V. (2024) · Figshare · doi:10.6084/m9.figshare.26577800
Additional file 21 of Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
Pelgrims, I., Devleesschauwer, B., Vandevijvere, S., Clercq, E. M. D., Vansteelandt, S., Gorasso, V., & der Heyden, J. V. (2024) · Figshare · doi:10.6084/m9.figshare.26577818
Additional file 11 of Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
Pelgrims, I., Devleesschauwer, B., Vandevijvere, S., Clercq, E. M. D., Vansteelandt, S., Gorasso, V., & der Heyden, J. V. (2024) · Figshare · doi:10.6084/m9.figshare.26577788
Additional file 1 of Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
Pelgrims, I., Devleesschauwer, B., Vandevijvere, S., Clercq, E. M. D., Vansteelandt, S., Gorasso, V., & der Heyden, J. V. (2024) · Figshare · doi:10.6084/m9.figshare.26577758
Additional file 3 of Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
Pelgrims, I., Devleesschauwer, B., Vandevijvere, S., Clercq, E. M. D., Vansteelandt, S., Gorasso, V., & der Heyden, J. V. (2024) · Figshare · doi:10.6084/m9.figshare.26577764
Additional file 1 of Multigenerational inequalities of opportunity in health outcomes
Balasooriya, N. N., Bandara, J. S., & Rohde, N. (2024) · Figshare · doi:10.6084/m9.figshare.26747471
Additional file 5 of Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
Pelgrims, I., Devleesschauwer, B., Vandevijvere, S., Clercq, E. M. D., Vansteelandt, S., Gorasso, V., & der Heyden, J. V. (2024) · Figshare · doi:10.6084/m9.figshare.26577770
Additional file 7 of Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
Pelgrims, I., Devleesschauwer, B., Vandevijvere, S., Clercq, E. M. D., Vansteelandt, S., Gorasso, V., & der Heyden, J. V. (2024) · Figshare · doi:10.6084/m9.figshare.26577776
Additional file 9 of Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
Pelgrims, I., Devleesschauwer, B., Vandevijvere, S., Clercq, E. M. D., Vansteelandt, S., Gorasso, V., & der Heyden, J. V. (2024) · Figshare · doi:10.6084/m9.figshare.26577782
Additional file 18 of Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
Pelgrims, I., Devleesschauwer, B., Vandevijvere, S., Clercq, E. M. D., Vansteelandt, S., Gorasso, V., & der Heyden, J. V. (2024) · Figshare · doi:10.6084/m9.figshare.26577809
Additional file 17 of Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
Pelgrims, I., Devleesschauwer, B., Vandevijvere, S., De Clercq, E. M., Vansteelandt, S., Gorasso, V., & der Heyden, J. V. (2024) · Figshare · doi:10.6084/m9.figshare.26577806
Additional file 13 of Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
Pelgrims, I., Devleesschauwer, B., Vandevijvere, S., Clercq, E. M. D., Vansteelandt, S., Gorasso, V., & der Heyden, J. V. (2024) · Figshare · doi:10.6084/m9.figshare.26577794
Additional file 4 of Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
Pelgrims, I., Devleesschauwer, B., Vandevijvere, S., Clercq, E. M. D., Vansteelandt, S., Gorasso, V., & der Heyden, J. V. (2024) · Figshare · doi:10.6084/m9.figshare.26577767
Additional file 2 of Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
Pelgrims, I., Devleesschauwer, B., Vandevijvere, S., Clercq, E. M. D., Vansteelandt, S., Gorasso, V., & der Heyden, J. V. (2024) · Figshare · doi:10.6084/m9.figshare.26577761
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Additional file 10 of Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
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Additional file 12 of Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
Pelgrims, I., Devleesschauwer, B., Vandevijvere, S., Clercq, E. M. D., Vansteelandt, S., Gorasso, V., & der Heyden, J. V. (2024) · Figshare · doi:10.6084/m9.figshare.26577791
Additional file 16 of Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
Pelgrims, I., Devleesschauwer, B., Vandevijvere, S., Clercq, E. M. D., Vansteelandt, S., Gorasso, V., & der Heyden, J. V. (2024) · Figshare · doi:10.6084/m9.figshare.26577803
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Authors: Stommel, M., & Schoenborn, C. A.
Affiliations: Michigan State University (US)
National Center for Health Statistics (US)
Corresponding author: Stommel, Manfred
ORCID: Stommel, Manfred
Venue: BMC Public Health
Publisher: Springer Science and Business Media LLC
Published: 2009-11-19
Volume: 9
Issue: 1
Pages: 421-421
ISSN: 1471-2458 (ISSN-L)
DOI: 10.1186/1471-2458-9-421
PMC: PMC2784464
OpenAlex: W2101246830
Cited by: 599
References: 25
Citations by year: 2026: 13 · 2025: 23 · 2024: 48 · 2023: 32 · 2022: 32 · 2021: 27 · 2020: 43 · 2019: 40 · 2018: 46 · 2017: 38 · 2016: 51 · 2015: 33 · 2014: 55 · 2013: 38 · 2012: 46
FWCI: 26.76
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/2.0 (tdm)
Locations: BMC Public Health (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders: Centers for Disease Control and Prevention
Topics: Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Health Sciences › Medicine › Physiology (medical) › Body Composition Measurement Techniques
Keywords: body mass index, self-reported height and weight, measurement error, obesity, overweight, sociodemographic predictors, health risk prediction, NHANES, NHIS
MeSH terms: Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Body Height, Body Weight, Female, Health Surveys, Humans, Male, Middle Aged, Nutrition Surveys, Obesity, Sex Factors, Socioeconomic Factors, United States, Reproducibility of Results, Body Mass Index, Young Adult

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Accuracy and usefulness of BMI measures based on self-reported weight and height: findings from the NHANES & NHIS 2001-2006

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